Team members: Yifei TangDonglin Jia
Mohan Wang
Wharton People Analytics Conference Case Competition
Project ObjectiveProject MethodologyKey Findings RecommendationsQ&A
Overview
2
Measure university performance based upon tier adjustments
Find the optimal tier and the best tier assignment for each university
Optimize recruiter resource allocation and maximize the number of qualified candidates
Project Objective
3
Tier 3 should cover more universities and the number of uncovered universities should be reduced
Tier 1 and Tier 2 should keep their current coverage
We suggest: Tier 1 : Tier 2 : Tier 3 = 83 : 81 : 208
Recommendations
4
Project Methodology
Transfer variables from student level to university level, to be used as indicators to measure productive universities
Cluster universities using Performance-Potential Matrix
Perform Lead Scoring Analysis to calculate expected number of qualified applicants
Leverage Large-scale Linear Programming to find optimal solution for recruiter resource allocation
5
2016 only 2017 only
126 279 12
Our Focus86 417
23
Target Universities
6
0204060
Number of schools
<5 5--10 10--1505
1015
Number of ap-plicants
We only focus 417 universities that add valueInactive universities: 86Unknown universities: 23
7
In 2017, accepted rate in tier 2 & 3 were roughly same to that in 2016, which could be further improved
Fine Tuned Tier Policy Is On The Right Track
Tier1 Tier 2 Tier 30
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
Accepted rate for each tier
20172016 20162017 2017
Evaluation Of Tier Policy Change
High Performance
High Potential
Low Potential
Low Performance
8
Improperly upgrade resulted in waste of recruiter resourceImproperly downgrade led to loss of potential candidates
Lead Scoring Model
Purpose: how many students can be hired from each university if it was NOT in its current tier?
Based upon the predicted number of students, optimize the allocation of recruiters
Example:University of Husky was in Tier-2 in 2016 and in Tier-1 in
2017. How many students can be hired from University of Husky if it was in Tier-2 in 2017? What if in Tier-3?
9
Segment Universities
Tier-2 Tier-2
Tier-3
None
Tier-1
2016 2017
#2#3
#1Similar features &increase rate
Predict which segment these universities belong to based on their features
Conversion Probability: If these universities were in Tier-1 in 2017, how likely the number of students hired would increase by a certain rate
10
Sample Coefficient Table
University
Tier 1 Tier 2 Tier 3 No Policy
# 1 43.00 29.83 25.83 0.00# 2 5.00 3.82 2.49 0.00# 3 12.00 4.19 1.43 0.00# 4 6.61 4.08 3.00 0.00
… … … … …
Generally speaking, the higher the tier, the more students can be hired
However, with limited recruiter resource and varied sensitivity to tiers of each university, we have to optimize the tier allocation to maximize the number of students can be hired 11
Tier 1 79
Tier 2118
Tier 394
No Policy 126
Large-scale Linear Optimization
Tier 183
Tier 281
Tier 3208
No Policy45
Optimized Allocation: Current Allocation:
Strategy #1: Tier 3 should cover more universities Strategy #2: Tier 1 & Tier 2 should keep their current coverage Number of students who accepted the offer is predicted to
increase by 28.1%, reaching 3059
12
Questions & Discussion
13
Top Related